The need for sustainable funding for Indigenous doula services in Canada
Bibliographic record
Abstract
OBJECTIVES: To interview representatives from Indigenous doulas across Canada in order to document how they manage the logistics of providing community-based doula care and understand their challenges. These objectives inform the development of an Indigenous doula pilot programme as part of the project, 'She Walks With Me: Supporting Urban Indigenous Expectant Mothers Through Culturally Based Doulas'. METHODS: In 2020, semi-structured interviews were conducted with members of five Indigenous doula collectives across Canada. Interview transcripts were approved by participants and subsequently coded by the entire research team to identify key themes. RESULTS: Our article explores one of the main themes that emerged from these interviews: sustainable funding for Indigenous doula services. Within this theme we identified two sub-themes: (1) limitations on and regulations for available funding and (2) negative impacts of limited funding on doula service. CONCLUSION: A major challenge to providing Indigenous community-based doula services is sustainable funding. Current models of funding for this work often do not provide livable wages and are bound by limited durations and regulations that are unsustainable and can be culturally inappropriate. Due to this lack of sustainable funding, Indigenous doula service in Canada faces challenges that include high staff turnover and burnout and lack of time and resources to provide culturally safe care, pursue professional development and additional training, and keep their services affordable for the families who need them. Future research is needed to ascertain potential programmes and funding streams for sustainable Indigenous doula support in Canada, including possible integration of doula care into the universal public health care system despite the jurisdictional challenges in providing health care for Indigenous peoples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.032 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".